Biases in Static Oligopoly Models?: Evidence from the California Electricity Market

Estimating market power is often complicated by a lack of reliable marginal cost data. Instead, policy-makers often rely on summary statistics of the market, thought to be correlated with price cost margins— such as concentration ratios or the HHI. In many industries, these summary statistics may be only weakly correlated with deviations from marginal cost pricing. Beginning with Gollop and Roberts (1979), a number of empirical studies identify industry competition and marginal cost levels by estimating the …rms’…rst order condition within a conjectural variations framework. Despite the prevalence of such “New Empirical Industrial Organization”(NEIO) studies, Corts (1999) illustrates the estimated mark-ups may be biased, since the estimated conjectural variations model forces the supply relationship to be a ray through the marginal cost intercept, whereas this need not be true in dynamic games. In this paper, we use direct measures of marginal cost for the California electricity market to measure the extent to which estimated mark-ups and marginal costs are biased. Our results suggest that the NEIO technique poorly estimates mark-ups and the sensitivity of marginal cost to cost shifters. We thank Severin Borenstein, Jim Bushnell, Erin Mansur, Steve Puller, Victor Stango and Catherine Wolfram for helpful comments. We also thank Severin Borenstein, Jim Bushnell and Frank Wolak for providing us with their marginal cost data. Kim gratefully acknowledges support from the California Energy Commission, while Knittel gratefully acknowledges support from the University of California Energy Institute. Kim: Korea Institute for Industrial Economics and Trade. Email: [email protected]. Knittel: Department of Economics, University of California, Davis, University of California Energy Institute and NBER. Email: [email protected].